遗传学测序依赖于从样本中提取DNA以进行扩增。
Genetic sequencing relies on extracting DNA from samples to amplify.
利用信道频率相关特性降低了算法复杂度，同时解决了算法对样本数的依赖问题。
The algorithm USES the channel correlation in the frequency domain to greatly reduce the computation complexity and the number of required samples.
参数方差的这一组成部分依赖于样本容量。
This components of parameter variance depends on the sample size.
它利用有限数量的观测来寻求待求的依赖关系，目标是在未来样本上的预测越准确越好。
It tries to extract the dependency rule from a finite number of examples, with the ultimate aim of predicting the future unknown samples as accurate as possible.
在计算中，采用的数据直接来源于样本，减少了对已有数据和经典概率分布的依赖。
The data adopted in calculation directly source from the samples, and thus the reliance on the existing data and the classical probability distribution functions is reduced.
传统的多因子疾病研究方法以及大样本前瞻性研究表明遗传因素在酒依赖发病过程中起重要作用。
Orthodox study mode on multiple factor disease and large sample perspective study indicate that hereditary factor is a considerable role in the process of alcohol dependence pathogenesis.
一般的动态聚类算法都是针对静态样本数据的，其聚类结果不仅依赖初始分类，而且易陷入局部极小。
The general dynamic clustering algorithms are used by static samples. The results of clustering not only rely on the original classification, but easily get into local optimum.
一般的动态聚类算法都是针对静态样本数据的，其聚类结果不仅依赖初始分类，而且易陷入局部极小。
The general dynamic clustering algorithms are used by static samples. The results of clustering not only rely on the original classification, but easily get into local optimum.
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